Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
An intrusion detection system gathers and tests information from different parts within a computer network to characterize possible security threats that include threats from both outside and inside of the organization. This system generates a large volume of alerts by detecting these threats which contains irrelevant and redundant attributes. Attribute selection, therefore is an important step in data mining. Most researches use all attributes in their databases while some of these features may be irrelevant or redundant and they do not participate to the process of intrusion detection. Therefore, different attribute ranking and attribute selection techniques are proposed. In this study, presented salient attributes mining technique according on improved principle component analysis algorithm which are utilized to select, rank reliable attributes and remove inefficient attributes to have a more precise and reliable intrusion detection process standard database.
How to cite this article:
Karim Hashim Al-Saedi. Toward Mining Salient Attributes Based on Developing Principle Component
Analysis Algorithm.
DOI: https://doi.org/10.36478/jeasci.2018.5890.5896
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2018.5890.5896